from core.codex_informer import CodexInformer
from core.eil_processor import EILProcessor
from core.esil_inference import ESILInference
from core.eris_reasoner import ERISReasoner
from core.hei_inference import HEIInference
from core.fec_controller import FECController
import yaml

def run_pipeline(user_input_text, force_hei=False):
    print("\n--- MEC MVP Test Run ---")
    print(f"[Main] Pipeline Input: {user_input_text}")

    # Load Response Strategies YAML
    with open('config/response_strategies.yaml', 'r', encoding='utf-8') as f:
        response_strategies = yaml.safe_load(f)['response_strategies']

    # 1️⃣ CodexInformer and EIL Processor (handles both normalization and emotion processing)
    codex_informer = CodexInformer()
    eil = EILProcessor(codex_informer)

    # Run emotion inference
    eil_packet = eil.infer_emotion(user_input_text)
    print(f"[Main] EIL Packet Output: {eil_packet}")

    # 2️⃣ ESIL Inference
    esil = ESILInference(codex_informer)
    esil_packet = esil.infer_esil(eil_packet)

    # 3️⃣ Forced HEI Mode: Ensure it forces the low confidence path if True
    if force_hei:
        print("\n[Main] FORCE HEI MODE ENABLED — Routing to HEI Inference")
        esil_packet['confidence_score'] = 0.40  # force low confidence to trigger HEI

    print(f"[Main] ESIL Packet Output: {esil_packet}")

    # Routing logic:
    if esil_packet['confidence_score'] >= 0.65:
        print("\n[Main] Routing: proceed_to_eris")
        # 4️⃣ ERIS Reasoning (Final UESP Creation)
        eris = ERISReasoner()
        final_uesp = eris.reason_emotion_state(esil_packet)
        print(f"[Main] ERIS Packet Output: {final_uesp}")

        # 5️⃣ FEC Controller (Final Fusion Prompt)
        fec = FECController()
        fusion_prompt = fec.generate_prompt(final_uesp)
        print(f"[Main] Final Fusion Prompt:\n{fusion_prompt}")

        # 6️⃣ Simulated Empathic Response
        fam_code = final_uesp.get('primary_emotion_code') or final_uesp.get('Primary Emotion Code')
        rsm_code = response_strategies.get(fam_code, {}).get('rsm_code', 'RSM-UNKNOWN')
        strategy_name = response_strategies.get(fam_code, {}).get('strategy', 'Strategy not defined')
        sample_response = response_strategies.get(fam_code, {}).get('sample_response', 'No response available')

        simulated_output = (
            f"Response Strategy Code: {rsm_code}\n"
            f"Response Strategy: {strategy_name}\n\n"
            f"{sample_response}"
        )

        print(f"\n[Main] Simulated Empathic Response:\n{simulated_output}")

    elif esil_packet['confidence_score'] < 0.65:
        print("\n[Main] Routing: escalate_to_hei")
        # 6️⃣ Trigger HEI Inference (Fallback for Low Confidence)
        hei = HEIInference()
        pseudo_esil = hei.detect_low_signal(esil_packet)
        print(f"[Main] Pseudo-ESIL Output:\n{pseudo_esil}")

        # 7️⃣ Post-HEI Path: Continue to ERIS → UESP → FEC
        print("\n[Main] Continuing to ERIS Reasoner (Post-HEI Path)")
        eris = ERISReasoner()
        final_uesp = eris.reason_emotion_state(pseudo_esil)
        print(f"[Main] ERIS Packet Output: {final_uesp}")

        fec = FECController()
        fusion_prompt = fec.generate_prompt(final_uesp)
        print(f"[Main] Final Fusion Prompt:\n{fusion_prompt}")

        # 8️⃣ Simulated Empathic Response
        fam_code = final_uesp.get('primary_emotion_code') or final_uesp.get('Primary Emotion Code')
        rsm_code = response_strategies.get(fam_code, {}).get('rsm_code', 'RSM-UNKNOWN')
        strategy_name = response_strategies.get(fam_code, {}).get('strategy', 'Strategy not defined')
        sample_response = response_strategies.get(fam_code, {}).get('sample_response', 'No response available')

        simulated_output = (
            f"Response Strategy Code: {rsm_code}\n"
            f"Response Strategy: {strategy_name}\n\n"
            f"{sample_response}"
        )

        print(f"\n[Main] Simulated Empathic Response:\n{simulated_output}")

    else:
        print("\n[Main] Routing: LLM Assist — Not implemented")

if __name__ == "__main__":
    # Example input that matches a SAL Trigger:
    test_input = "I am feeling joy"

    # Run in FORCE HEI mode → set to True to test Symbolic Layer
    run_pipeline(test_input, force_hei=False)